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<tr class="memdesc:"><td class="mdescLeft"> </td><td class="mdescRight"><a class="el" href="../../d5/d08/classcv_1_1cuda_1_1BufferPool.html" title="BufferPool for use with CUDA streams. ">BufferPool</a> for use with CUDA streams.  <a href="../../d5/d08/classcv_1_1cuda_1_1BufferPool.html#details">More...</a><br/></td></tr>
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<tr class="memdesc:"><td class="mdescLeft"> </td><td class="mdescRight">Class that enables getting cudaEvent_t from <a class="el" href="../../d5/d38/classcv_1_1cuda_1_1Event.html">cuda::Event</a>.  <a href="../../da/d71/structcv_1_1cuda_1_1EventAccessor.html#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td align="right" class="memItemLeft" valign="top">struct  </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dc/dec/structcv_1_1cuda_1_1GpuData.html">cv::cuda::GpuData</a></td></tr>
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<tr class="memdesc:"><td class="mdescLeft"> </td><td class="mdescRight">Class that enables getting cudaStream_t from <a class="el" href="../../d9/df3/classcv_1_1cuda_1_1Stream.html" title="This class encapsulates a queue of asynchronous calls. ">cuda::Stream</a>.  <a href="../../d6/df1/structcv_1_1cuda_1_1StreamAccessor.html#details">More...</a><br/></td></tr>
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Functions</h2></td></tr>
<tr class="memitem:ga3a55474eb59c884697edf397fe0f871c"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d9/d41/group__cudacore__struct.html#ga3a55474eb59c884697edf397fe0f871c">cv::cuda::createContinuous</a> (int rows, int cols, int type, <a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> arr)</td></tr>
<tr class="memdesc:ga3a55474eb59c884697edf397fe0f871c"><td class="mdescLeft"> </td><td class="mdescRight">Creates a continuous matrix.  <a href="../../d9/d41/group__cudacore__struct.html#ga3a55474eb59c884697edf397fe0f871c">More...</a><br/></td></tr>
<tr class="separator:ga3a55474eb59c884697edf397fe0f871c"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ga4551c222cdf97ebdb4d7440fecfc737a"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d9/d41/group__cudacore__struct.html#ga4551c222cdf97ebdb4d7440fecfc737a">cv::cuda::ensureSizeIsEnough</a> (int rows, int cols, int type, <a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> arr)</td></tr>
<tr class="memdesc:ga4551c222cdf97ebdb4d7440fecfc737a"><td class="mdescLeft"> </td><td class="mdescRight">Ensures that the size of a matrix is big enough and the matrix has a proper type.  <a href="../../d9/d41/group__cudacore__struct.html#ga4551c222cdf97ebdb4d7440fecfc737a">More...</a><br/></td></tr>
<tr class="separator:ga4551c222cdf97ebdb4d7440fecfc737a"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ga6d25da8194cc95035994ae98e9eebc02"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d9/d41/group__cudacore__struct.html#ga6d25da8194cc95035994ae98e9eebc02">cv::cuda::registerPageLocked</a> (<a class="el" href="../../d3/d63/classcv_1_1Mat.html">Mat</a> &amp;m)</td></tr>
<tr class="memdesc:ga6d25da8194cc95035994ae98e9eebc02"><td class="mdescLeft"> </td><td class="mdescRight">Page-locks the memory of matrix and maps it for the device(s).  <a href="../../d9/d41/group__cudacore__struct.html#ga6d25da8194cc95035994ae98e9eebc02">More...</a><br/></td></tr>
<tr class="separator:ga6d25da8194cc95035994ae98e9eebc02"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ga93da1d4c64558590950409266b1e2a92"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d9/d41/group__cudacore__struct.html#ga93da1d4c64558590950409266b1e2a92">cv::cuda::setBufferPoolConfig</a> (int deviceId, size_t stackSize, int stackCount)</td></tr>
<tr class="separator:ga93da1d4c64558590950409266b1e2a92"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ga7dbf253e43493eb870c9759cc35bbffb"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d9/d41/group__cudacore__struct.html#ga7dbf253e43493eb870c9759cc35bbffb">cv::cuda::setBufferPoolUsage</a> (bool on)</td></tr>
<tr class="memdesc:ga7dbf253e43493eb870c9759cc35bbffb"><td class="mdescLeft"> </td><td class="mdescRight"><a class="el" href="../../d5/d08/classcv_1_1cuda_1_1BufferPool.html" title="BufferPool for use with CUDA streams. ">BufferPool</a> management (must be called before <a class="el" href="../../d9/df3/classcv_1_1cuda_1_1Stream.html" title="This class encapsulates a queue of asynchronous calls. ">Stream</a> creation)  <a href="../../d9/d41/group__cudacore__struct.html#ga7dbf253e43493eb870c9759cc35bbffb">More...</a><br/></td></tr>
<tr class="separator:ga7dbf253e43493eb870c9759cc35bbffb"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ga68dd974fb5e19f6306122a4b49c6a428"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d9/d41/group__cudacore__struct.html#ga68dd974fb5e19f6306122a4b49c6a428">cv::cuda::unregisterPageLocked</a> (<a class="el" href="../../d3/d63/classcv_1_1Mat.html">Mat</a> &amp;m)</td></tr>
<tr class="memdesc:ga68dd974fb5e19f6306122a4b49c6a428"><td class="mdescLeft"> </td><td class="mdescRight">Unmaps the memory of matrix and makes it pageable again.  <a href="../../d9/d41/group__cudacore__struct.html#ga68dd974fb5e19f6306122a4b49c6a428">More...</a><br/></td></tr>
<tr class="separator:ga68dd974fb5e19f6306122a4b49c6a428"><td class="memSeparator" colspan="2"> </td></tr>
</table>
<a id="details" name="details"></a><h2 class="groupheader">Detailed Description</h2>
<h2 class="groupheader">Function Documentation</h2>
<a id="ga3a55474eb59c884697edf397fe0f871c"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ga3a55474eb59c884697edf397fe0f871c">◆ </a></span>createContinuous()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void cv::cuda::createContinuous </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>rows</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>cols</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>type</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> </td>
          <td class="paramname"><em>arr</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>arr</td><td>=</td><td>cv.cuda.createContinuous(</td><td class="paramname">rows, cols, type[, arr]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p><code>#include &lt;<a class="el" href="../../d8/dd1/modules_2core_2include_2opencv2_2core_2cuda_8hpp.html">opencv2/core/cuda.hpp</a>&gt;</code></p>
<p>Creates a continuous matrix. </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">rows</td><td>Row count. </td></tr>
    <tr><td class="paramname">cols</td><td>Column count. </td></tr>
    <tr><td class="paramname">type</td><td>Type of the matrix. </td></tr>
    <tr><td class="paramname">arr</td><td>Destination matrix. This parameter changes only if it has a proper type and area ( \(\texttt{rows} \times \texttt{cols}\) ).</td></tr>
  </table>
  </dd>
</dl>
<p>Matrix is called continuous if its elements are stored continuously, that is, without gaps at the end of each row. </p>
</div>
</div>
<a id="ga4551c222cdf97ebdb4d7440fecfc737a"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ga4551c222cdf97ebdb4d7440fecfc737a">◆ </a></span>ensureSizeIsEnough()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void cv::cuda::ensureSizeIsEnough </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>rows</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>cols</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>type</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> </td>
          <td class="paramname"><em>arr</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>arr</td><td>=</td><td>cv.cuda.ensureSizeIsEnough(</td><td class="paramname">rows, cols, type[, arr]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p><code>#include &lt;<a class="el" href="../../d8/dd1/modules_2core_2include_2opencv2_2core_2cuda_8hpp.html">opencv2/core/cuda.hpp</a>&gt;</code></p>
<p>Ensures that the size of a matrix is big enough and the matrix has a proper type. </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">rows</td><td>Minimum desired number of rows. </td></tr>
    <tr><td class="paramname">cols</td><td>Minimum desired number of columns. </td></tr>
    <tr><td class="paramname">type</td><td>Desired matrix type. </td></tr>
    <tr><td class="paramname">arr</td><td>Destination matrix.</td></tr>
  </table>
  </dd>
</dl>
<p>The function does not reallocate memory if the matrix has proper attributes already. </p>
</div>
</div>
<a id="ga6d25da8194cc95035994ae98e9eebc02"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ga6d25da8194cc95035994ae98e9eebc02">◆ </a></span>registerPageLocked()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void cv::cuda::registerPageLocked </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../d3/d63/classcv_1_1Mat.html">Mat</a> &amp; </td>
          <td class="paramname"><em>m</em></td><td>)</td>
          <td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.cuda.registerPageLocked(</td><td class="paramname">m</td><td>)</td></tr></table>
</div><div class="memdoc">
<p><code>#include &lt;<a class="el" href="../../d8/dd1/modules_2core_2include_2opencv2_2core_2cuda_8hpp.html">opencv2/core/cuda.hpp</a>&gt;</code></p>
<p>Page-locks the memory of matrix and maps it for the device(s). </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">m</td><td>Input matrix. </td></tr>
  </table>
  </dd>
</dl>
</div>
</div>
<a id="ga93da1d4c64558590950409266b1e2a92"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ga93da1d4c64558590950409266b1e2a92">◆ </a></span>setBufferPoolConfig()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void cv::cuda::setBufferPoolConfig </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>deviceId</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">size_t </td>
          <td class="paramname"><em>stackSize</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>stackCount</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.cuda.setBufferPoolConfig(</td><td class="paramname">deviceId, stackSize, stackCount</td><td>)</td></tr></table>
</div><div class="memdoc">
<p><code>#include &lt;<a class="el" href="../../d8/dd1/modules_2core_2include_2opencv2_2core_2cuda_8hpp.html">opencv2/core/cuda.hpp</a>&gt;</code></p>
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<h2 class="memtitle"><span class="permalink"><a href="#ga7dbf253e43493eb870c9759cc35bbffb">◆ </a></span>setBufferPoolUsage()</h2>
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          <td class="memname">void cv::cuda::setBufferPoolUsage </td>
          <td>(</td>
          <td class="paramtype">bool </td>
          <td class="paramname"><em>on</em></td><td>)</td>
          <td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.cuda.setBufferPoolUsage(</td><td class="paramname">on</td><td>)</td></tr></table>
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<p><code>#include &lt;<a class="el" href="../../d8/dd1/modules_2core_2include_2opencv2_2core_2cuda_8hpp.html">opencv2/core/cuda.hpp</a>&gt;</code></p>
<p><a class="el" href="../../d5/d08/classcv_1_1cuda_1_1BufferPool.html" title="BufferPool for use with CUDA streams. ">BufferPool</a> management (must be called before <a class="el" href="../../d9/df3/classcv_1_1cuda_1_1Stream.html" title="This class encapsulates a queue of asynchronous calls. ">Stream</a> creation) </p>
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<h2 class="memtitle"><span class="permalink"><a href="#ga68dd974fb5e19f6306122a4b49c6a428">◆ </a></span>unregisterPageLocked()</h2>
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          <td class="memname">void cv::cuda::unregisterPageLocked </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../d3/d63/classcv_1_1Mat.html">Mat</a> &amp; </td>
          <td class="paramname"><em>m</em></td><td>)</td>
          <td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.cuda.unregisterPageLocked(</td><td class="paramname">m</td><td>)</td></tr></table>
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<p><code>#include &lt;<a class="el" href="../../d8/dd1/modules_2core_2include_2opencv2_2core_2cuda_8hpp.html">opencv2/core/cuda.hpp</a>&gt;</code></p>
<p>Unmaps the memory of matrix and makes it pageable again. </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">m</td><td>Input matrix. </td></tr>
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